International Trade, Risk and the Role of Banks Friederike Niepmann and Tim Schmidt-Eisenlohr Federal Reserve Board The views expressed in this presentation are those of the authors and do not necessarily reflect the position of the Federal Reserve Board or the Federal Reserve System. Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 1 / 32
Motivation International trade is risky and takes time Optimal payment contracts, Schmidt-Eisenlohr (2013) Cash-in-advance Open account Letter of credit Some evidence on cash-in-advance versus open account: Antras and Foley (2011), Hoefele et al. (2012), Demir and Javorcik (2014) Very little evidence on bank trade finance - letter of credit and similar guarantees - Glady and Potin (2011), Federico and del Prete (2012) No analysis of other bank trade finance products - documentary credit Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 2 / 32
Motivation II This paper, focus on bank trade finance: letters of credit (LC) and documentary collections (DC): Perceived to be a large business, but hard to quantify Little reliable or comprehensive data Surveys by IMF-BAFT, ICC High policy relevance: basically all development banks have trade finance programs, e.g. IFC $5 billion for LC confirmation Key questions: How large is bank trade finance? How does it vary across countries? What are the key factors? What is the difference between letters of credit and documentary collections? Do they behave differently? Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 3 / 32
This Paper I First data on U.S. bank trade finance from two unique sources (1) U.S. regulatory data: Long horizon, quarterly data: 1997-2012 By destination country and bank (2) SWIFT message data Distinguishes between documentary collections and letters of credit Long time horizon: number of messages sent Short time horizon: values of messages sent By destination country Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 4 / 32
Main Results I Trade finance business: U.S. trade finance is large Letters of credit: 8.8 percent of U.S. exports Documentary collections: about 1.2 percent of U.S. exports Trade finance business highly concentrated: Top 5 banks hold more than 90 percent of claims Patterns I: Letter of credit use Increases in the time to trade (time to import and distance) Is hump-shaped in destination country rule of law - intermediate risk countries use LCs the most Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 5 / 32
Main Results II Patterns II: Documentary collections use Increases in the time to trade Is linearly increasing in destination country rule of law Patterns III: Relative importance of letters of credit to documentary credit declines in destination country rule of law Average transaction size: largest for LCs, intermediate for DCs, smallest for standerd (open account or cash in advance) trade transaction Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 6 / 32
Implications Our results have implications for: Payment choice model Needs to be modified to generate hump-shape of LCs Endogenous letter of credit fee Introduce documentary collection Trade costs Increase in the time to trade (risk channel - additional to working capital channel) Transmission of financial shocks Should be heterogeneous across countries Main focus of Niepmann and Schmidt-Eisenlohr (2013) Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 7 / 32
Cross-country Patterns Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 8 / 32
Trade finance intensity (TFI) of top trading partners 40% 35% 30% SWIFT Values as Percentage of Exports by Top 20 US Export Destinations MT400 (DC) MT700 (LC) Ranked Left to Right by US Export Share 25% 20% 15% 10% 5% 0% Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 9 / 32
Top countries in terms of trade finance intensity (TFI) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% LC and DC Intensities for Top 10 Countries Top countries in letter of credit intensity MT400 (DC) MT700 (LC) Top countries in documentary collection intensity Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 10 / 32
A Model of Payment Contract Choice Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 11 / 32
Cash in Advance and Open Account Cash in Advance First: Importer pays Then: Exporter delivers no risk for exporter Open Account First: Exporter delivers Then: Importer pays full risk for exporter Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 12 / 32
Documentary Credit I 2. Export goods Exporter 1. Sales Contract Importer 3. Submit Documents 8. Payment 5. Payment 6. Deliver Documents Advising Bank (Exporter s) 7. Payment Issuing Bank (Importer s) 4. Send Documents Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 13 / 32
Documentary Credit II DC reduces risk of non-payment Requires paying fee to banks of f DC Lower risk for exporter than with Open Account Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 14 / 32
Letter of Credit I Contract Execution 1. Contract 5. Shipment 4. Authenticate letter of credit. 2. Apply for letter of credit. 9. Payment 6. Submit documents. 7. Send documents. 11. Release documents. 10. Payment 3. Send letter of credit. 8. Payment Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 15 / 32
Letter of Credit II LC reduces risk of non-payment even more than DC more screening, banks sometimes require cash deposits Providing a letter of credit implies: i) fixed monitoring cost: m ii) cost of guaranteeing payment (expected loss) LC implies even less risk for exporter than DC but a higher cost Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 16 / 32
Profits of payment types against destination enforcement 0.5 0.45 0.4 CIA OA LC DC Profits 0.35 0.3 0.25 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 λ * Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 17 / 32
Hump shape I Proposition 2 Letters of credit and documentary collections have the highest relative profitability at intermediate values of λ. Profitability advantage 0.02 0.018 0.016 0.014 0.012 0.01 0.008 0.006 0.004 DC LC 0.002 0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 λ * Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 18 / 32
Hump shape II Introduce a random multiplicative shock with mean one for each payment contract Simulate the model and show the shares of different payment contracts for different λ Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 19 / 32
Hump shape III 0.7 0.6 0.5 CIA OA LC DC Share 0.4 0.3 0.2 0.1 0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 λ * Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 20 / 32
Payment forms and transaction sizes LCs and DCs imply some fixed costs that are independent of transaction size with m > F DC This gives rise to increasing returns to scale. Show this in a graph where we vary total revenues R, keeping constant the ratio R/K = 1.5 Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 21 / 32
Payment forms and transaction sizes II Share 0.0 0.1 0.2 0.3 0.4 CIA OA LC DC 0.5 1.0 1.5 2.0 2.5 3.0 Revenues Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 22 / 32
Country Heterogeneity I: Rule of Law Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 23 / 32
Trade finance and rule of law Main measure World Bank World Governance indicators: Rule of Law Results robust to using alternative measures Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 24 / 32
Trade finance and rule of law (1) (2) (3) (4) (5) lntf lntf lntrafficlc lntrafficdc log(# SWIFT mct) log(exports ct) 1.022*** 1.039*** 0.896*** 0.896*** 0.877*** (0.0439) (0.0533) (0.0609) (0.0581) (0.0433) log(distance c) 0.651*** 0.414** 0.710*** 1.314*** 0.943*** (0.184) (0.186) (0.171) (0.366) (0.178) rule of law ct -2.291*** 6.967*** 7.361*** 12.49*** 5.419*** (0.441) (2.284) (2.740) (3.598) (1.690) rule of law 2 ct -7.667*** -7.304*** -5.961** -5.613*** (2.072) (2.101) (2.696) (1.289) DC message dummy mct -3.455*** (0.433) rule of law ct * DC dummy mct 5.055*** (0.658) rule of law 2 ct * DC dummy mct log(gdp per cap ct) -0.745-1.291 1.075-0.434 (0.792) (0.780) (0.963) (0.536) log(gdp per cap ct) 2 0.0425 0.0556-0.0738 0.00857 (0.0520) (0.0481) (0.0589) (0.0332) fin. development ct 0.00373 0.588*** 0.0609 0.422*** (0.141) (0.174) (0.215) (0.146) Time FE Yes Yes Yes Yes Yes Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 25 / 32
Trade finance and rule of law II log(messages) -2-1 0 1 2 0.2.4.6.8 1 rule of law DC messages LC messages Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 26 / 32
Hump shape III 0.7 0.6 0.5 CIA OA LC DC Share 0.4 0.3 0.2 0.1 0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 λ * Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 27 / 32
Transactions Sizes Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 28 / 32
Average transaction sizes (2011/2012) All exports/number of transactions: $ 42k Documentary credit value / numbers: $ 136k Letters of credit value / numbers: $ 656k Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 29 / 32
Time to trade Additional results on distance and time to trade LC use increases in distance and time to trade evidence that long distance trade is inherently riskier Effects of risk on LC choice only matter for countries with above median distance from U.S. Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 30 / 32
Conclusions Letters of credit about 9 percent of U.S. exports LC use is heterogeneous across countries: hump-shaped in rule of law DC use is linearly increasing in rule of law Findings fully consistent with an extended model of payment contract choice low use of LCs in riskiest countries may result from an optimal decision, not a supply constraint Policy relevant to understand heterogeneity because it affects trade costs transmission of financial shocks DCs are not good substitute for LCs. They behave more similar to open account and do not seem to be able to reduce risk a lot in countries with bad enforcement Fixed costs seem to be substantial for LCs much higher average transaction value Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 31 / 32
Thank you for your attention and comments! Niepmann, Schmidt-Eisenlohr (Fed) U.S. trade finance 32 / 32